{"id":"W4294725370","doi":"10.1111/mec.16683","title":"Collective and harmonized high throughput barcoding of insular arthropod biodiversity: Toward a Genomic Observatories Network for islands","year":2022,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Environment Research Council; European Commission; Sight Research UK","keywords":"Biodiversity; Biology; Arthropod; DNA barcoding; Ecology; Data science; Evolutionary biology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003301454,0.0003718922,0.0003921436,0.00283561,0.0008270303,0.00155033,0.001141993,0.0006925664,0.001687879],"category_scores_gemma":[0.006618514,0.0002098691,0.0003881136,0.003296113,0.0008506035,0.002229437,0.004099271,0.00101284,0.0004600933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001323164,"about_ca_system_score_gemma":0.002649354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01277776,"about_ca_topic_score_gemma":0.02684045,"domain_scores_codex":[0.9990446,0.0002679054,0.0000613316,0.0003461255,0.0001629696,0.0001170487],"domain_scores_gemma":[0.9958391,0.0008132751,0.0008528921,0.0008225848,0.001135669,0.0005366042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002228914,0.0001150094,0.2620346,0.001196948,0.0003356953,0.0005802651,0.007792391,0.03417759,0.03635899,0.05542676,0.03099589,0.5707629],"study_design_scores_gemma":[0.00003470814,0.0002136963,0.2973696,0.0008790658,0.0003471056,0.0005046366,0.01016936,0.2343098,0.01644378,0.1578297,0.281719,0.0001794576],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.284007,0.003085454,0.6696115,0.005966323,0.0003051285,0.0004514154,0.01805563,0.002582234,0.01593535],"genre_scores_gemma":[0.4879106,0.001202391,0.4859837,0.0007372553,0.0001346053,0.0005556779,0.01980269,0.0002626154,0.003410374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01277776,"threshold_uncertainty_score":0.02540672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0267714869328879,"score_gpt":0.2215616465439361,"score_spread":0.1947901596110483,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}